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AWS re:Invent 2022 Announcements for AWS Machine Learning Engineers and Data Scientists

2023-04-27T03:58:46+00:00

Every year, professionals all around the world attend the most transformative tech event —  AWS re:Invent. Here, a LOT of new AWS services and capabilities are announced and discussed. In this post, we will focus on the major announcements relevant to data scientists and ML engineers! A Gentle Introduction to Amazon SageMaker The major announcements discussed in this post focus on SageMaker, so we will spend a paragraph or two quickly talking about the service.  Amazon SageMaker is the machine learning platform of AWS that helps solve a variety of requirements of data scientists, developers, and machine learning practitioners in [...]

AWS re:Invent 2022 Announcements for AWS Machine Learning Engineers and Data Scientists2023-04-27T03:58:46+00:00

Getting Started with SageMaker Ground Truth Private Workforce

2023-07-08T07:25:35+00:00

Before we begin, let’s quickly talk about what Amazon SageMaker is and what it is used for. If this is your first time learning about Amazon SageMaker, it is the machine learning platform of AWS that helps solve the different requirements of data scientists, developers, and machine learning practitioners.  It has several features and capabilities that assist in the different stages of the machine learning process. In this tutorial, we will focus on SageMaker Ground Truth and how it helps data science teams get access to clean labeled datasets.  When performing machine learning experiments, getting access to labeled datasets is [...]

Getting Started with SageMaker Ground Truth Private Workforce2023-07-08T07:25:35+00:00

Scalable Data Processing and Transformation using SageMaker Processing (Part 2 of 2)

2023-04-28T02:18:41+00:00

In this 2-part tutorial, we will focus on SageMaker Processing and how we can use it to solve our data processing needs. Our overall goal is to demonstrate how to use SageMaker Processing to help us perform Min-Max scaling on a dataset in its own dedicated and easily scalable environment.  If you are looking for Part 1, you can find it here. As mentioned in Part I, we have divided this tutorial into 4 sections: [1] Synthetic Data Generation (found in PART I) [2] Using MinMaxScaler without the managed infrastructure support of SageMaker Processing (found in PART I) [3] Using [...]

Scalable Data Processing and Transformation using SageMaker Processing (Part 2 of 2)2023-04-28T02:18:41+00:00

Amazon SageMaker

2023-10-14T02:18:09+00:00

Bookmarks Concepts Common Training Data Formats For Built-in Algorithms Input modes for transferring training data Two methods of deploying a model for inference SageMaker features Optimization Amazon SageMaker Monitoring Amazon SageMaker Pricing Validate Your Knowledge Amazon SageMaker Cheat Sheet A fully managed service that allows data scientists and developers to easily build, train, and deploy machine learning models at scale. Provides built-in algorithms that you can immediately use for model training. Also supports custom algorithms through docker containers. One-click model deployment. Concepts Hyperparameters It refers to a set [...]

Amazon SageMaker2023-10-14T02:18:09+00:00

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